Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ScONE-seq: A one-tube single-cell multi-omics method enables simultaneous dissection of genotype and phenotype heterogeneity from frozen tumor samples

ABSTRACT: Both the genotypic and phenotypic cellular heterogeneity play important roles in normal tissue function as well as disease development. To be able to characterize these different forms of cellular heterogeneity in diverse types of samples, we developed scONE-seq, which enables simultaneous transcriptome and genome profiling in a one-tube reaction. We demonstrate the feasibility of scONE-seq by benchmarking it against existing methods using cell lines and lymphocytes from a healthy donor. Furthermore, we applied scONE-seq to a frozen years-old IDH1-mutant glioblastoma (GBM) sample and profiled over 1200 nuclei from a single sample, subsequently identifying a phenotypically normal-like tumor clone that was only distinguishable by superimposing paired clonal and transcriptomic data.

ORGANISM(S): Homo sapiens

PROVIDER: GSE185269 | GEO | 2022/12/31

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Combinatorial genetic strategy accelerates the discovery of cancer genotype-phenotype associations [scDNA-seq_MOI]

Project description:Available genetically-defined cancer models are limited in genotypic and phenotypic complexity and underrepresent the heterogeneity of human cancer. Herein, we describe a combinatorial genetic strategy applied to an organoid transformation assay to rapidly generate diverse, clinically relevant models of bladder and prostate cancer. Importantly, the clonal architecture of the resultant tumors can be resolved using single-cell or spatially resolved next-generation sequencing to uncover polygenic drivers of cancer phenotypes.

2023-12-01 | GSE231543 | GEO

Combinatorial genetic strategy accelerates the discovery of cancer genotype-phenotype associations [DNA-seq_distribution]

2023-12-01 | GSE231542 | GEO

Combinatorial genetic strategy accelerates the discovery of cancer genotype-phenotype associations [scDNA-Seq]

2023-12-01 | GSE229782 | GEO

Combinatorial genetic strategy accelerates the discovery of cancer genotype-phenotype associations [RNA-Seq]

2023-12-01 | GSE229780 | GEO

Combinatorial genetic strategy accelerates the discovery of cancer genotype-phenotype associations [bulk DNA-Seq]

2023-12-01 | GSE229781 | GEO

scONE-seq: A single-cell multi-omics method enables simultaneous dissection of phenotype and genotype heterogeneity from frozen tumors.

Project description:Single-cell multi-omics can provide a unique perspective on tumor cellular heterogeneity. Most previous single-cell whole-genome RNA sequencing (scWGS-RNA-seq) methods demonstrate utility with intact cells from fresh samples. Among them, many are not applicable to frozen samples that cannot produce intact single-cell suspensions. We have developed scONE-seq, a versatile scWGS-RNA-seq method that amplifies single-cell DNA and RNA without separating them from each other and hence is compatible with frozen biobanked samples. We benchmarked scONE-seq against existing methods using fresh and frozen samples to demonstrate its performance in various aspects. We identified a unique transcriptionally normal-like tumor clone by analyzing a 2-year frozen astrocytoma sample, demonstrating that performing single-cell multi-omics interrogation on biobanked tissue by scONE-seq could enable previously unidentified discoveries in tumor biology.

| S-EPMC9812385 | biostudies-literature

scONE-seq: A one-tube single-cell multi-omics method enables simultaneous dissection of genotype and phenotype heterogeneity from frozen tumor samples

Project description:scONE-seq: A one-tube single-cell multi-omics method enables simultaneous dissection of genotype and phenotype heterogeneity from frozen tumor samples

| PRJNA768428 | ENA

Benchmarking dataset for measurement and removal of index hopping artifacts in multiplexed droplet-based single-cell RNA-seq data

Project description:Sample index hopping refers to the incorrect sample assignment of a demultiplexed sequencing read in a library pool. To enable benchmarking of methods for measurement of index hopping rate and removal of its artifacts in single-cell RNA-seq data, we developed a validation dataset consisting of a multiplexed library of two samples, in which the true sample of origin of most reads are known. The reads with known sample of origin provide the ground truth for measuring the performance of index hopping correcting methods.

2020-05-09 | GSE149087 | GEO

Roles of female and male genotype in post-mating responses in Drosophila melanogaster

Project description:Purpose: Mating induces a multitude of changes in female behavior, physiology and gene expression. Interactions between female and male genotype lead to variation in post-mating phenotypes and reproductive success. So far, few female molecules responsible for these interactions have been identified. Methods: We used Drosophila melanogaster from five geographically dispersed populations to investigate such female x male genotypic interactions at the female transcriptomic and phenotypic levels. Methods: Females from each line were singly-mated to males from the same five lines, for a total of 25 combinations. To assess whether female x male genotypic interactions affect the female post-mating transcriptome, next-generation RNA sequencing was performed on virgin and mated females at 5 to 6 hours post-mating. Results: Seventy-seven genes showed strong variation in mating-induced expression changes in a female x male genotype-dependent manner. These genes were enriched for immune response and odorant-binding functions, and for expression exclusively in the head. Conclusions: The transcriptional variation found in specific functional classes of genes might be a read-out of female x male compatibility at a molecular level. Understanding the roles these genes play in the female post-mating response will be crucial to better understand the evolution of post-mating responses and related conflicts between the sexes.

2017-10-10 | GSE104706 | GEO

Label-free Quantitative Acetylomics Revealed Toxoplasma gondii Genotype-Specific Acetylome Signatures

Project description:Distinct genotypic and pathogenicity differences exist between strains of the opportunistic protozoan Toxoplasma gondii. The label-free quantitative acetylomics approach was applied to investigate the differences in the level of acetylation between RH strain, PRU strain and PYS strain of T. gondii. The results showed that lysine acetylation in RH strain was the largest (458 acetylated proteins) among the three strains. The PYS strain had the second-largest acetylome (188 acetylated proteins), whereas lysine acetylation in PRU strain (115 acetylated proteins) was the smallest. Motif analysis revealed four, three and four motifs enriched from lysine acetylation sequences in RH strain, PRU strain and PYS strain respectively, suggesting specificity of acetyltransferases in these strains. Our analysis also identified 15 DAPs (differentially expressed acetylated proteins), 3 DAPs and 26 DAPs in RH strain vs PRU strain, PRU strain vs PYS strain and PYS strain vs RH strain, respectively. Compared with PYS strain and PRU strain, histone acetyltransferase and glycyl-tRNA synthase had higher expression levels in RH strain, reflecting genotype-specific differences in stress tolerance. These findings provide novel insight into the acetylomic profiles of major genotypes of T. gondii and provide an important resource for further analysis of the roles of the acetylated parasite proteins in the regulation of cellular functions.

2020-05-27 | PXD015031 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data